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AI Architect
HTC Global Services
Abu Dhabi, UAE
Contract
Mid-Senior
Onsite
Discovered 3 weeks ago
Agentic AIGenerative AILarge language modelsLLM orchestrationRetrieval-augmented generationVector databases
Free
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Agentic AIGenerative AILarge language models
Role Overview
HTC Global Services is hiring an AI Architect for a one-year extendable contract in Abu Dhabi, United Arab Emirates.
The role is onsite and focuses on designing, building, and deploying production-grade enterprise AI solutions.
Key Skills for This Role
Agentic AIGenerative AILarge language modelsLLM orchestrationRetrieval-augmented generationVector databases
Full Job Posting
Role Overview
HTC Global Services is hiring an AI Architect for a one-year extendable contract in Abu Dhabi, United Arab Emirates.
The role is onsite and focuses on designing, building, and deploying production-grade enterprise AI solutions.
Technical Skills and Expertise
- Design and deploy agentic AI applications using autonomous and multi-agent workflows, planning, reasoning, memory, tools, and human-in-the-loop systems.
- Apply LLM implementation patterns including prompt engineering, structured outputs, function and tool calling, context management, and model selection.
- Design and optimize RAG pipelines with document ingestion, chunking, embeddings, vector search, reranking, context optimization, and grounded responses.
- Use LLM orchestration frameworks and patterns such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
- Work with vector databases and search technologies such as Azure AI Search, Pinecone, Weaviate, Milvus, pgvector, FAISS, or similar platforms.
- Build and integrate MCP servers, tools, resources, and AI-agent integrations.
- Integrate AI agents with enterprise applications, APIs, databases, and external tools using REST, GraphQL, SDKs, function calling, and event-driven architectures.
- Implement guardrails, content filtering, prompt-injection protection, PII protection, access controls, human approval workflows, and responsible AI practices.
- Define AI evaluation, benchmarking, hallucination detection, quality metrics, tracing, monitoring, and feedback loops.
- Optimize trade-offs among latency, quality, reliability, scalability, and cost.
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